Abstract
In this paper we propose very efficient itemset representation for frequent itemset mining from transactional databases. The combinatorial number system is used to uniquely represent frequent k-itemset with just one integer value, for any k>=2. Experiments show that memory requirements can be reduced up to 300
Keywords
MSC
68P20, 68P30, 68T30
Cite this article
@article{cai-3716,
author = {Savo Tomović and Predrag Stanišić},
title = {An Efficient Itemset Representation for Mining Frequent Patterns in Transactional Databases},
journal = {Computing and Informatics},
volume = {37},
number = {4},
pages = {894--914},
year = {2018},
issn = {1335-9150},
doi = {10.4149/cai_2018_4_894}
}
TY - JOUR AU - Savo Tomović AU - Predrag Stanišić TI - An Efficient Itemset Representation for Mining Frequent Patterns in Transactional Databases JO - Computing and Informatics VL - 37 IS - 4 SP - 894 EP - 914 PY - 2018 SN - 1335-9150 DO - 10.4149/cai_2018_4_894 UR - https://doi.org/10.4149/cai_2018_4_894 KW - Frequent itemset mining KW - Apriori algorithm KW - combinatorial number system ER -
Tomović, S., & Stanišić, P. (2018). An Efficient Itemset Representation for Mining Frequent Patterns in Transactional Databases. Computing and Informatics, 37(4), 894–914. https://doi.org/10.4149/cai_2018_4_894